Modeling the avoidance behavior of zooplankton on phytoplankton infected by free viruses

Nutrient enrichment and phytoplankton toxicity influence a diversity of complex dynamics in a fear-induced plankton-fish model

In this paper, we contemplate the dynamics of an aquatic system consisting of three interacting species, phytoplankton, zooplankton, and fish. We assume that the evading risk of fish predation induces fear in zooplankton species, which affects its growth dynamics radically. On the other hand, zooplankton develop an anti-predator defense by taking temporary refuge. Interestingly, the system potentially exhibits multi-stable configurations under identical ecological conditions by allowing different bifurcation scenarios, including multiple saddle-node and transcritical bifurcations with varying levels of nutrients, strength of phytoplankton toxicity, zooplankton refuge size and the cost of fear imposed by fish population. Further, by adding Gaussian white noise, we have extended the deterministic system to its stochastic version. We find that white noise appears to regulate the survival and extinction of model species. Comprehensive numerical simulations are consistent with mathematical results prognosticated by linear analysis. Overall, our study may provide a new insight into the mechanisms of emergence and mitigation of plankton blooms.

Catastrophic and noncatastrophic population crashes in a bitrophic system with dynamic additional food provision to cooperative predators

In this article we contemplate the dynamics of an additional food-provided prey-predator system. We assume that the behavior of cooperative predators induces fear in prey, which radically affects the prey's birth and death rates. We observe that the structural instability imposed by strong cooperative hunting among predators goes away with higher intensities of fear levels affecting the prey's reproductive output and mortality. High levels of prey refuge are not conducive to the survival of predators. In such a situation, adequate supply of high-quality additional food is favorable regarding the persistence and stability of the system. Interestingly, the system potentially exhibits two stable configurations under identical ecological conditions by allowing different bifurcation scenarios, including saddle-node and backward bifurcations, and associated hysteresis effects with prey refuge along with additional food quantity and quality. In the stochastic environment, the system experiences critical transitions through bifurcation-induced tipping events with time-varying additional food for predators. Enhanced disturbance events promote noise-induced switching and tipping events. Finally, our investigation explores whether impending population crashes resulting from the variability of additional food quantity and quality can reliably be predicted using early warning signals in the context of redshifted noise. Overall, our results may provide insights for finding control strategies in the context of community ecology.

Evolutionarily stable strategies to overcome Allee effect in predator-prey interaction

Every successful species invasion is facilitated by both ecological and evolutionary mechanisms. The evolution of population's fitness related traits acts as functional adaptations to Allee effects. This trade-off increases predatory success at an expense of elevated death rate of potential predators. We address our queries employing an eco-evolutionary modeling approach that provides a means of circumventing inverse density-dependent effect. In the absence of evolution, the ecological system potentially exhibits multi-stable configurations under identical ecological conditions by allowing different bifurcation scenarios with the Allee effect. The model predicts a high risk of catastrophic extinction of interacting populations around different types of saddle-node bifurcations resulting from the increased Allee effect. We adopt the game-theoretic approach to derive the analytical conditions for the emergence of evolutionarily stable strategy (ESS) when the ecological system possesses asymptotically stable steady states as well as population cycles. We establish that ESSs occur at those values of adopted evolutionary strategies that are local optima of some functional forms of model parameters. Overall, our theoretical study provides important ecological insights in predicting successful biological invasions in the light of evolution.

Toxicity-mediated regime shifts in a contaminated nutrient-plankton system

In this article, we contemplate the dynamics of a three-tier system of nutrient, phytoplankton, and zooplankton with a gestation delay of discrete type and a distributed delay in nutrient recycling. Phytoplankton secretion-mediated alteration in the grazing pattern of zooplankton is encapsulated by a Monod-Haldane functional response. We carry out global sensitivity analysis for identifying the crucial model parameters having a significant impact on zooplankton density. The system potentially exhibits bistable configurations under identical ecological conditions by allowing different bifurcation scenarios, including multiple saddle-node and transcritical bifurcations with varying input rates of nutrients and inhibitory effects of phytoplankton against zooplankton. We observe that the gestation delay in zooplankton is responsible for the emergence of noxious bloom events. Interestingly, when the delay parameter crosses a threshold, the system experiences chaotic disorder, which prognosticates the onset of irregular bloom. Furthermore, by adding Gaussian white noise, we have extended the deterministic model to its stochastic counterpart. We found that white noise appears to regulate the survival and extinction of interacting populations. Comprehensive numerical simulations are consistent with mathematical results prognosticated by linear analysis.

Pelagic Bacteria and Viruses in a High Arctic Region: Environmental Control in the Autumn Period

In the marine environment, bacteria and viruses play a significant role in carbon fluxes, remineralization processes, and the infection of various organisms. We performed a survey in the northeastern Barents Sea, a region adjacent to the Arctic Ocean, to investigate spatial patterns of microbial plankton, after the main productive period, in October 2020. Two main water masses occurred in the study region—colder Arctic Water and warmer Barents Sea Water, representing transformed Atlantic Water. Multivariate analyses detected patchiness in the horizontal distribution of bacteria and viruses, and their abundances showed no clear association with the water masses. There was an obvious vertical pattern in microbial concentration, with the highest estimates in the upper layers. Surface viral and bacterial abundance varied in a wide range (2.20 × 105−10.7 × 105 cells·mL−1 and 0.86 × 106−14.98 × 106 particles·mL−1, respectively) and were correlated with each other. Bacterioplankton was dominated by small-sized cells (<2 μm, 0.04−0.06 µm3), and the average volume of bacterial cells tended to increase toward the seafloor. The ratio of viral to bacterial abundance (VBR) was 11 ± 1 and did not differ between water masses and depth layers. VBR were higher, compared to summer values, suggesting a strong impact of viruses on bacterioplankton, after the main productive season. Redundancy and correlation analyses showed that inorganic nutrients (nitrate and phosphate) and organic carbon from zooplankton were most responsible for the total variability in the microbial parameters. Water temperature and salinity, also, had a measurable impact, but their influence was lower. Bacterial abundance was lower than in other seasons and regions of the Barents Sea, while viral abundance was comparable, suggesting a stronger viral impact on Arctic marine bacteria in the autumn season.

MATHEMATICAL ANALYSIS AND NUMERICAL SIMULATION OF A NONLINEAR DYNAMICAL MODEL FOR THE COEXISTENCE OF AGRICULTURE AND MINING IN RURAL AREAS

Agriculture and mining get interlinked with each other when they take place concurrently in rural parts of the world. In order to explore it in mathematical terms, a nonlinear dynamical model system is proposed in this study with agricultural yield, human population and mining as system variables. The agricultural yield is assumed to have logistic growth and also, supplements rural human population growth. Mining is assumed to be not only advancing with constant rate, but also getting induced through rural human population. The model is qualitatively analyzed for the identification of different equilibrium states and their stability behaviors. The model analysis reveals the conditions under which agriculture and mining together with rural population can achieve a stable system. These qualitative findings are substantiated with quantitative results, under which sensitiveness of different parameters of the model towards the model outcomes are investigated through global sensitivity analysis technique. Also, bifurcation parameters and their critical values are determined to predict the states of qualitative behavioral change. The results suggest that a balanced system can be obtained by taking measures to control unconducive mining and augment agricultural outputs.